• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.105-106
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• 2014

본 논문에서는 중요도 지도를 사용한 화소값 사이 척력 기반 영상 대조비 향상 기법을 제안한다. 공간상에서 인접한 화소들 사이에 자주 발생하는 화소값들의 차이를 크게 하면 효과적으로 영상의 디테일을 두드러지게 할 수 있다. 대조비 증가를 위해 화소값 사이 척력을 정의하고, 유효 화소값 사이 척력들의 합을 사용하여 대조비의 증가 정도를 조절한다. 중요도 지도는 영상의 화소마다 사람의 시선이 머무르는 정도를 상대적인 수치로 나타낸 것이다. 따라서 영상 화질을 개선할 때 중요도 지도를 사용하면 사람의 시선을 끄는 화소값들의 대조비를 선택적으로 높일 수 있다. 실험 결과를 통하여 제안 기법이 우수한 화질개선 영상을 생성함을 확인한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.139-141
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• 2022

As interest in digital video media and intelligent systems increases rapidly, technologies using video information are being combined and used in various fields such as security and artificial intelligence. Impulse noise generated during digital image processing degrades the image quality of the image and reduces the reliability of information, so it is necessary to remove it through a filter. There are SMF, AWMF, and MDBUTMF as well-known antecedent methods, but they all have limitations in achieving seamless filtering in environments with large loss of information on valid pixels due to problems with the algorithm itself. Therefore, this paper designs a median filter algorithm that applies weights reflecting the reliability of the information by searching for the nearest effective pixels present within the mask. For performance evaluation, this algorithm and the preceding algorithm were compared and analyzed using PSNR and enlarged images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.251-258
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• 2004

This paper proposes a method for estimating the illuminant chromaticity using the distributions of the camera responses obtained by a CCD camera in a real-world scene. Illuminant estimation using a highlight method is based on the geometric relation between a body and its surface reflection. In general, the pixels in a highlight region are affected by an illuminant geometric difference, camera quantization errors, and the non-uniformity of the CCD sensor. As such, this leads to inaccurate results if an illuminant is estimated using the pixels of a CCD camera without any preprocessing. Accordingly, to solve this problem the proposed method analyzes the distribution of the CCD camera responses and selects pixels using the Mahalanobis distance in highlight regions. The use of the Mahalanobis distance based on the camera responses enables the adaptive selection of valid pixels among the pixels distributed in the highlight regions. Lines are then determined based on the selected pixels with r-g chromaticity coordinates using a principal component analysis(PCA). Thereafter, the illuminant chromaticity is estimated based on the intersection points of the lines. Experimental results using the proposed method demonstrated a reduced estimation error compared with the conventional method.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.591-594
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• 2003

본 논문은 중심 화소의 FOD 성분값과 인접 가해 성분값의 평균으로 축소 성분값을 산출함으로써 FOD에 적응성을 부여한 디지털 영상 축소 알고리즘의 성능을 분석함에 그 목적이 있다. 제안된 방법은, 중심 화소의 우측 및 하측 인접 화소의 기울기의 크기를 이용하여 산출한 각각의 국부 가해 가중치를 우측 및 하측 인접 화소값에 곱한 후에 그 결과를 합산함으로써 인접 가해 성분값을 구하고 FOD 성분값과 이 인접 가해 성분값을 평균하여 축소 성분값을 구하는 과정을 전체 영역에 반복적으로 수행함으로써 축소 영상을 얻을 수 있다. 제안된 축소 방법에 따르면, 적은 연산량을 요하면서도 평균적으로 우수한 결과를 제공하는 FOD 방식의 장점을 취하면서 인접 화소의 유효 가해 성분을 각각의 국부 가해 가중치에 따라 축소 성분값에 적응적으로 반영함으로써 FOD의 단점인 몽롱화 현상을 효과적으로 억제시킬 수 있는 바, 개선된 정보 보존성을 제공할 수 있는 이점이 있다. 본고에서는 주관적인 성능과 하드웨어 복잡도 측면에서 제안된 방법과 기존의 각 방식에 대한 성능을 분석 평가한다.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.57-73
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• 1997

This paper is related to the correction of radiometric distortions induced by topographic relief. RADARSAT SAR image data were obtained over the mountainous area near southern part of Seoul. Initially, the SAR data was geometrically corrected and registered to plane rectangular coordinates so that each pixel of the SAR image has known topographic parameters. The topographic parameters (slope and aspect) at each pixel position were calculated from the digital elevation model (DEM) data having a comparable spatial resolution with the SAR data. Local incidence angle between the incoming microwave and the surface normal to terrain slope was selected as a primary geometric factor to analyze and to correct the radiometric distortions. Using digital maps of forest stands, several fields of rather homogeneous forest stands were delineated over the SAR image. Once the effects of local incidence angle on the radar backscatter were defined, the radiometric correction was performed by an empirical fuction that was derived from the relationship between the geometric parameters and mean radar backscatter. The correction effects were examined by ground truth data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.989-995
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• 2022

Currently, the demand for image processing is increasing due to the development of IT technology, and active research is being conducted. Since image data generates image noise due to various external causes, and thus degrades the performance of the image, noise removal is essential. Salt and Pepper noise is a representative image noise, and various studies are being conducted to remove it. Existing algorithms include A-TMF, AFMF, LIWF, but these have the disadvantage that their performance is somewhat insufficient. Therefore, in this paper, we propose an algorithm that performs filtering using linear interpolation with effective pixels existing around the central pixel only in case of noise after performing noise judgment in order to efficiently remove salt and pepper noise. In order to judge the performance of the proposed algorithm, it was compared using the processed image of the previously studied algorithm and PSNR.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.305-315
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• 2010

In this paper, a frequentistic approach to impute the values of R, G, B-components in random missing pixels of color image is provided. Under assumption that the given image is a realization of Gaussian Markov random field, its model is designed such that each neighbor pixel values for a given pixel follows (independently) the normal distribution with covariance matrix scaled by an evaluates of the similarity between two pixel values, so that the imputation is not to be affected by the neighbors with different color. An approximate EM-based algorithm maximizing the underlying likelihood is implemented to estimate the parameters and to impute the missing pixel values. Some experiments are presented to show its effectiveness through performance comparison with a popular interpolation method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.674-677
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• 2017

The Hough transform is the most representative algorithm for a straight line detection based on edge pixels. It shows excellent performance in a simple linear image but requires a considerable amount of computation in a noisy or complex image and has a problem of detecting a pseudo straight line easily. In this paper, we propose a straight line detection algorithm to solve the problem of the conventional Hough transform. The proposed algorithm detects the straight line information of edge pixels by using principal component analysis (PCA) before performing Hough transform and performs the Hough transform of the limited slope area in the valid edge pixels based on the detected straight line information of edge pixels. Simulation results show that the proposed algorithm reduces the amount of computation as well as eliminates pseudo straight lines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.179-181
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• 2018

Digital imaging equipment is used for a variety of purposes in a wide range of fields in society and is becoming an important element of the 4th industrial revolution. Imaging equipment data is exposed to noise from various causes, and this noise affects accuracy of the equipment, causing errors and lowering reliability. In the present paper, an algorithm based on directional effective pixels is proposed to effectively remove high-density Salt and Pepper noise. Conventional methods show that performance decreases as Salt and Pepper noise density increases. To the contrary, the proposed method has noise-removal performance superior to those of conventional methods, by performing de-noising which considers directional effective pixels even in a high-density Salt and Pepper noise environment. Experimental results show that the proposed algorithm is superior to the existing methods, and performance is verified through enlarged images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1320-1326
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• 2018

Digital video equipment is important in the 4th industrial revolution and is widely used in different fields for various purpose. Data of digital video equipment is exposed to noise due to different reasons including user environment and processing and such noise affect output and processing method. This can even cause error, resulting in decreased reliability of the equipment. In this research, it offers algorithm to effectively recover video by removing noise and impulse noise occurring during the process of channel delivery. This proposed algorithm recovers video by exploring valid pixel using directional local mask and noise determination. Then, valid pixel calculated goes through the final output calculation through comparative analysis on estimation. For comparing suggested method and algorithm, simulation is carried out. For checking the function of it, PSNR and profile are analyzed.